Problem generation model training method, problem generation method and related equipment thereof

Abstract

The embodiment of the invention belongs to the field of artificial intelligence, and relates to a problem generation model training method, a problem generation method and related equipment. The method comprises the following steps: pre-training an initial model to obtain a pre-trained language model, and adjusting a mask matrix in pre-training to realize three language models; obtaining questionand answer information including a question text and an answer text; extracting a key entity related to the question text from the answer text; setting a network in the pre-trained language model to adapt to Chinese text generation; inputting the key entity and the answer text into a pre-training language model to obtain a prediction question text; determining a prediction error according to the prediction problem text and the problem text; and adjusting the model according to the prediction error to obtain a problem generation model. Data annotation does not need to depend on manpower. In addition, the invention also relates to a blockchain technology, and the prediction problem text can be stored in the blockchain node.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular, to a training method of a problem generation model, a problem generation method and related equipment. Background technique [0002] With the development of natural language processing technology, question generation technology has emerged. How to generate natural language-based questions is an important topic in the field of natural language processing. Question generation has a wide range of applications. For example, machine knowledge bases can use active questioning to build or supplement knowledge bases and expand data sets; in the field of education, question generation can help students to ask questions; in the field of dialogue, question generation can be used as a cold start to start A topic, or getting feedback by asking questions, the application scenarios are very rich. [0003] Existing problem generation technologies are usually based o...

AI Technical Summary

Problems solved by technology

[0003] Existing question generation technologies are usually based on known grammar rules, use grammar trees to generate questions, and fill existing templates with entities in the knowledge base. This technology has poor transferability and requires A large amount of prior expert knowledge; Another technique is to use a deep learning model to generate questions based on pre-labeled answers. This technology requires a large amount of manual labeling in advance, which is time-consuming and laborious, and most of the labeled text is short, which affects the problem. generation

It can be seen that the existing question generation technology has poor performance in generating questions.

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